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will include: Assemble and validate modular electrocatalytic reactors and analysis methods for realistic CO2 electrocatalysis, with a focus on parallel investigations and accelerated aging. Dissect
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system for thin, durable structural interventions. It can be deployed through conventional casting for standard applications and through 3D printing for complex or non-planar geometries. In parallel
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complex or non-planar geometries. In parallel, circular end-of-life strategies will recover fibres, upcycle fines into new low-carbon constituents, and enable structural reuse. The project comprises 11
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programming skills and strong hands-on experience implementing, training, and evaluating deep-learning models and research codebases. A strong track record in machine learning or closely related fields
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of modern deep-learning architectures and training strategies, and experience designing and rigorously evaluating new machine-learning methods. • Excellent Python programming skills and strong hands
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programming (e.g. Python or MATLAB) is an asset. A self-motivated and organized working style, with the ability to work independently while contributing effectively to an interdisciplinary and
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assays. Experience in catalysis, programming and large data analysis is a plus. Excellent communication skills and fluency in English (written and oral). Our offer The project is planned for 3 years
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processing Have preferably experience using ML models and tools (e.g. radiomics) in image processing and very good skills in programming Fluent in English, (German is beneficial) then, this position might
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programming Interest in lab-automation and working with agentic AI (e.g. Claude Code, Codex) Excellent communication skills in English Strong academic track-record and publication history The
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advantageous. Programming and data analysis skills in Python, MATLAB, R, or similar are advantageous. Proficiency in English; German is a plus. Enthusiasm for interdisciplinary research and